Bulk processing of optically scanned music

Bainbridge, D., Wijaya, K. (1999) 7th International Conference on Image Processing and its Applications,Manchester, UK, pp 474-478.

For many years now Optical Music Recognition (OMR) has been advocated as the leading methodology for transferring the bast repositories of music notation from paper to digital database–see for example Alphonce et al.(1), Carter (2), Clarke et al.(3), and Couasnon et al.(4). Other techniques exist for acquiring music on-line; however, these methods require operators with musical and computer skills. The notion, therefore, of an entirely automated process through OMR is highly attractive. It has been an active area of research since its inception in 1996 (Pruslin (5)), and even though there has been the development of many systems with impressively high accuracy rates (see Selfridge-Field for a survey (6)) it is surprising to note that there is little evidence of large collections being processed with the technology–work by Carter being the only known notable exception (7, 8). This paper outlines some of the insights gained, and algorithms implemented, through the practical experience of converting collections in excess of 400 pages. In doing so, the work demonstrates that there are additional factors not currently considered by other research centres that are necessary for OMR to reach its full potential.